code: def train(self, data):
      data_chunks = np.array_split(data, len(self.nodes), axis=1)
  
      res = []
      for n, d in zip(self.nodes, data_chunks):
          res.append(
              n.train.remote(
                  {
                      "obs": d[:, :, :-1],
                      "target": d[:, :, 1:],
                  }
              )
          )
  
      res = ray.get(res)
  
      loss = []
      last_loss = []
  
      for r in res:
          loss.append(r[0])
          last_loss.append(r[1])
  
      return np.array(loss).mean(), np.array(last_loss).mean()
  
file_path: mesh-transformer-jax/mesh_transformer/TPU_cluster.py
imports: import itertools
  import json
  import time
  import ray
  from typing import Callable
  import numpy
  from mesh_transformer.train_actor import NetworkRunner
  from google.cloud import storage
  from smart_open import open
  from func_timeout import func_set_timeout
label_desc: Use image node_id 2 for calling the TPUCluster obj's underlying member method code with example usage: obj.train(data) and returns: np,  np